#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
#

import abc
import numpy as np
from typing import Union, Dict, Optional, Any, List

class BaseModel(abc.ABC):
    def __init__(self, **knobs):
        pass

    @abc.abstractmethod
    def train(self, dataset_path: str, **train_args):
        raise NotImplementedError()

    @abc.abstractmethod
    def evaluate(self, dataset_path: str) -> float:
        raise NotImplementedError()

    @abc.abstractmethod
    def predict(self, queries: List[Any]) -> List[Any]:
        raise NotImplementedError()

    @abc.abstractmethod
    def save(self, path):
        raise NotImplementedError()

    @abc.abstractmethod
    def load(self, path):
        raise NotImplementedError()

    def destroy(self):
        pass

    @staticmethod
    def teardown():
        pass
